Construction and validation of a prognostic model based on 11 lymph node metastasis-related genes for overall survival in endometrial cancer

Identification of an HLA-A*11:01-restricted neoepitope of mutant PIK3CA and its specific T cell receptors for cancer immunotherapy targeting hotspot driver mutations

Hotspot driver mutations presented by human leukocyte antigens might be recognized by anti-tumor T cells. Based on their advantages of tumor-specificity and immunogenicity, neoantigens derived from hotspot mutations, such as PIK3CAH1047L, may serve as emerging targets for cancer immunotherapies. NetMHCpan V4.1 was utilized for predicting neoepitopes of PIK3CA hotspot mutation. Using in vitro stimulation, antigen-specific T cells targeting the HLA-A*11:01-restricted PIK3CA mutation were isolated from healthy donor-derived peripheral blood mononuclear cells. T cell receptors (TCRs) were cloned using single-cell PCR and sequencing. Their functionality was assessed through T cell activation markers, cytokine production and cytotoxic response to cancer cell lines pulsed with peptides or transduced genes of mutant PIK3CA. Immunogenic mutant antigens from PIK3CA and their corresponding CD8+ T cells were identified. These PIK3CA mutation-specific CD8+ T cells were subsequently enriched, and their TCRs were isolated. The TCR clones exhibited mutation-specific and HLA-restricted reactivity, demonstrating varying degrees of functional avidity. Identified TCR genes were transferred into CD8+ Jurkat cells and primary T cells deficient of endogenous TCRs. TCR-expressing cells demonstrated specific recognition and reactivity against the PIK3CAH1047L peptide presented by HLA-A*11:01-expressing K562 cells. Furthermore, mutation-specific TCR-T cells demonstrated an elevation in cytokine production and profound cytotoxic effects against HLA-A*11:01+ malignant cell lines harboring PIK3CAH1047L. Our data demonstrate the immunogenicity of an HLA-A*11:01-restricted PIK3CA hotspot mutation and its targeting therapeutic potential, together with promising candidates of TCR-T cell therapy.

Deciphering comprehensive features of tumor microenvironment controlled by chromatin regulators to predict prognosis and guide therapies in uterine corpus endometrial carcinoma

Background

Dysregulation of chromatin regulators (CRs) can perturb the tumor immune microenvironment, but the underlying mechanism remains unclear. We focused on uterine corpus endometrial carcinoma (UCEC) and used gene expression data from TCGA-UCEC to investigate this mechanism.

Methods

We used weighted gene co-expression network analysis (WGCNA) and consensus clustering algorithm to classify UCEC patients into Cluster_L and Cluster_H. TME-associated CRs were identified using WGCNA and differential gene expression analysis. A CR risk score (CRRS) was constructed using univariate Cox and LASSO-Cox regression analyses. A nomogram was developed based on CRRS and clinicopathologic factors to predict patients' prognosis.

Results

Lower CRRS was associated with lower grade, more benign molecular subtypes, and improved survival. Patients with low CRRS showed abundant immune infiltration, a higher mutation burden, fewer CNVs, and better response to immunotherapy. Moreover, low CRRS patients were more sensitive to 24 chemotherapeutic agents.

Conclusion

A comprehensive assessment of CRRS could identify immune activation and improve the efficacy of UCEC treatments.

Overexpression of HMGB3 and its prognostic value in breast cancer

Background

High mobility group protein B3 (HMGB3) is abundantly expressed in a number of malignancies, contributing to tumor cell growth and predicting poor outcomes. More research on the connection between HMGB3 and breast cancer is needed. The prognostic significance of HMGB3 in breast cancer was examined and validated in this study.

Methods

Using The Cancer Genome Atlas (TCGA) database RNA sequencing and clinical data, we investigated the associations between HMGB3 expression and tumor mutations, prognosis, and immune infiltration in breast cancer. The Gene Expression Profiling Interactive Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), breast cancer gene-expression miner (bc-GenExMiner), UALCAN, OncoLnc, cBio Cancer Genomics Portal (cBioPortal), and LinkedOmics databases were applied to examine the levels of expression, mutation, coexpression, and immune correlation of HMGB3 in breast cancer. cBioPortal and the Database for Annotation, Visualization, and Integrated Discovery (DAVID) were used for coexpression and enrichment analyses, respectively. Experimental tests and a separate cohort of breast cancer patients in our center were used for validation. To determine independent risk factors affecting breast carcinoma prognosis, multivariate Cox regression analysis was performed. The Kaplan-Meier method was applied to analyze the connection between HMGB3 expression and overall survival time in breast cancer.

Results

Pan-cancer investigation using the GEPIA and UALCAN databases revealed a high level of HMGB3 expression in different malignancies, including breast cancer. HMGB3 might be a potential diagnostic biomarker, according to the receiver operating characteristic (ROC) curve (AUC=0.932). And immunohistochemistry confirmed higher HMGB3 protein expression in breast cancer tissues in clinical samples. Experimental tests also showed that breast cancer cells have higher expression of HMGB3, and knockdown of HMGB3 can promote the proliferation of breast cancer cells and increase sensitivity to chemotherapy. Human epidermal growth factor receptor 2 (HER2), Nottingham Prognostic Index (NPI), basal-like status, nodal status (N+), triple-negative status, and Scarff-Bloom-Richardson (SBR) grade all showed positive correlations with HMGB3 expression. Conversely, HMGB3 expression was negatively associated with the expression of estrogen receptor (ER) and progesterone receptor (PR) in breast cancer. Breast cancer patients with high HMGB3 expression had poor overall survival, which was validated by an analysis of a separate cohort of breast cancer patients in our center. Cox regression analysis identified high HMGB3 expression as an independently associated risk factor for breast carcinoma. The amount of immunological infiltration was substantially linked with the high expression of HMGB3. The chromosome centromeric region, ATPase activity, and the cell cycle are critical areas where HMGB3 is involved, according to enrichment analysis. Therefore, we suspected that HMGB3 might be a potential biomarker for detecting and treating breast carcinoma.

Conclusion

Breast cancer tissues had higher HMGB3 expression than normal breast tissues. HMGB3 overexpression may serve as an indicator for poor breast cancer outcomes.

Construction and validation of a prognostic model based on 11 lymph node metastasis-related genes for overall survival in endometrial cancer

BACKGROUND

Endometrial cancer (EC) is one of the most common malignant tumors in female reproductive system. The incidence of lymph node metastasis (LNM) is only about 10% in clinically suspected early-stage EC patients. Discovering prognostic models and effective biomarkers for early diagnosis is important to reduce the mortality rate.

METHODS

A least absolute shrinkage and selection operator (LASSO) regression was conducted to identify the characteristic dimension decrease and distinguish porgnostic LNM related genes signature. Subsequently, a novel prognosis-related nomogram was constructed to predict overall survival (OS). Survival analysis was carried out to explore the individual prognostic significance of the risk model and key gene was validated in vitro.

RESULTS

In total, 89 lymph node related genes (LRGs) were identified. Based on the LASSO Cox regression, 11 genes were selected for the development of a risk evaluation model. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better OS (p = 3.583e-08). The area under the ROC curve (AUC) of this model was 0.718 at 5 years of OS. Then, we developed an OS-associated nomogram that included the risk score and clinicopathological features. The concordance index of the nomogram was 0.769. The survival verification performed in three subgroups from the nomogram demonstrated the validity of the model. The AUC of the nomogram was 0.787 at 5 years OS. Proliferation and metastasis of HMGB3 were explored in EC cell line. External validation with 30 patients in our hospital showed that patients with low-risk scores had a longer OS (p-value = 0.03). Finally, we revealed that the most frequently mutated genes in the low-risk and high-risk groups are PTEN and TP53, respectively.

CONCLUSIONS

Our results suggest that LNM plays an important role in the prognosis, and HMGB3 was potential as a biomarker for EC patients.